Videos captured from different cameras, at different times of day, or with varied light conditions can have a varying color consistency, or color cast. Varying color cast can cause a movie that is created from different videos to have an inconsistent look and feel. Consequently, significant work is required to manually edit individual videos to ensure the color cast of a movie remains consistent throughout. Typically, an editor is required to manually adjust parameters such as brightness, exposure, and color, for each video that is assembled into a movie. But such work is time consuming and tedious.
Existing solutions for automatically adjusting color across videos only examine global features and therefore provide suboptimal results by, for example, ignoring local variations such as features that are specific to different tonal ranges. For instance, different regions of video frames can be illuminated differently from other regions. Existing solutions fail to detect such variations and consequently fail to accurately propagate color consistency between videos. Other solutions use algorithms that cannot account for unusual color mismatches between videos and therefore give sub-optimum results.
Accordingly, solutions are needed for automatically suggesting changes to improve color consistency across videos.